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CEC
2010
IEEE
14 years 10 months ago
Cooperative Co-evolution with delta grouping for large scale non-separable function optimization
— Many evolutionary algorithms have been proposed for large scale optimization. Parameter interaction in nonseparable problems is a major source of performance loss specially on ...
Mohammad Nabi Omidvar, Xiaodong Li, Xin Yao
AI
2004
Springer
14 years 9 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu
WEBI
2005
Springer
15 years 3 months ago
Improving Web Clustering by Cluster Selection
Web page clustering is a technology that puts semantically related web pages into groups and is useful for categorizing, organizing, and refining search results. When clustering ...
Daniel Crabtree, Xiaoying Gao, Peter Andreae
ICRA
2005
IEEE
210views Robotics» more  ICRA 2005»
15 years 3 months ago
Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling
— Recently Rao-Blackwellized particle filters have been introduced as effective means to solve the simultaneous localization and mapping (SLAM) problem. This approach uses a par...
Giorgio Grisetti, Cyrill Stachniss, Wolfram Burgar...
CEC
2008
IEEE
15 years 4 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...